Using Passively Represented Information to Identify Items Within a Multi-Dimensional Space

ABSTRACT

A system, method, and computer-readable medium for accessing information associated with items within a multi-dimensional space, comprising: scanning a plurality of multi-dimensional symbols, each of the plurality of multi-dimensional symbols being scanned from a plurality of angles; identifying each of the plurality of multi-dimensional symbols for each angle; and storing information identifying each of the plurality of multi-dimensional symbols for each angle in an encoded geometry repository.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to information handling systems. Morespecifically, embodiments of the invention relate to using passivelyrepresented information to identify items within a multi-dimensionalspace.

Description of the Related Art

As the value and use of information continues to increase, individualsand businesses seek additional ways to process and store information.One option available to users is information handling systems. Aninformation handling system generally processes, compiles, stores,and/or communicates information or data for business, personal, or otherpurposes thereby allowing users to take advantage of the value of theinformation. Because technology and information handling needs andrequirements vary between different users or applications, informationhandling systems may also vary regarding what information is handled,how the information is handled, how much information is processed,stored, or communicated, and how quickly and efficiently the informationmay be processed, stored, or communicated. The variations in informationhandling systems allow for information handling systems to be general orconfigured for a specific user or specific use such as financialtransaction processing, airline reservations, enterprise data storage,or global communications. In addition, information handling systems mayinclude a variety of hardware and software components that may beconfigured to process, store, and communicate information and mayinclude one or more computer systems, data storage systems, andnetworking systems.

It is known to use information handling systems and related IT systemswithin information technology (IT) environments such as data centers. Insuch IT environments it is often desirable to be able to identifyindividual information handling systems and related IT systems. A knownmethod of identifying these systems is associating a unique identifiersuch as a bar code or a quick response (QR) code with the system. Thisunique identifier is often visibly attached to the system so that theunique identifier may be accessed by an IT technician using a scanner.However, unique identifiers such as bar codes and QR codes are notaesthetically pleasing, don't blend in with the system, can be scratchedoff or damaged, and involve extra processes to label objects.

SUMMARY OF THE INVENTION

A system, method, and computer-readable medium for facilitating decodingof information associated with items within a multi-dimensional space,comprising: scanning a plurality of multi-dimensional symbols, each ofthe plurality of multi-dimensional symbols being scanned from aplurality of angles; identifying each of the plurality ofmulti-dimensional symbols for each angle; and storing informationidentifying each of the plurality of multi-dimensional symbols for eachangle in an encoded geometry repository.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be better understood, and its numerousobjects, features and advantages made apparent to those skilled in theart by referencing the accompanying drawings. The use of the samereference number throughout the several figures designates a like orsimilar element.

FIG. 1 shows a general illustration of components of an informationhandling system as implemented in the system and method of the presentinvention.

FIG. 2 shows a block diagram of a physical part identificationenvironment.

FIG. 3 shows a high level flow chart of a physical part identificationgeneration operation.

FIG. 4 shows a high level flow chart of a physical part detectionoperation.

FIG. 5 shows a front view of an example encoded geometry.

FIG. 6 shows a flow chart of a multi-dimensional encoded geometrygeneration operation.

FIG. 7 shows line drawing views of example encoded geometries.

FIG. 8A shows a line drawing showing an example of how a glyph may beencoded.

FIG. 8B shows an example of a physical glyph corresponding to the glyphencoded according to the line drawing of FIG. 8A.

FIG. 9 shows a front view of a plurality of example encoded geometries.

FIG. 10 shows a perspective view of portions of a plurality of encodedgeometries.

FIG. 11 shows a depth scanning representation from scanning of portionsof a plurality of encoded geometries.

FIG. 12 shows a cloud point data representation from scanning ofportions of a plurality of encoded geometries.

FIG. 13 shows an overlay representation of information obtained fromscanning of portions of a plurality of encoded geometries.

FIGS. 14A and 14B, generally referred to as FIG. 14, show diagrammaticrepresentations of a passively represented information environment.

FIG. 15 shows a flow chart of an encoded geometry association operation.

FIG. 16 shows a flow chart of physical part detection operation.

FIG. 17 shows a flow chart of a multi-dimensional geometry trainingoperation.

FIG. 18 shows a flow chart of a multi-dimensional geometry decodingoperation.

FIG. 19 shows a diagrammatic representation of use of an AugmentedReality device when decoding an encoded geometry.

DETAILED DESCRIPTION

A system, method, and computer-readable medium are disclosed forperforming a physical part detection operation. In certain embodiments,the physical part detection operation includes decoding an encodedgeometry, comprising: scanning an encoded geometry, the scanningcomprising scanning a plurality of multi-dimensional symbols of theencoded geometry; identifying each of the plurality of multi-dimensionalsymbols; decoding each identifier multi-dimensional symbol to provideencoded geometry information; accessing an encoded geometry repository;and, retrieving data associated with the encoded geometry information.

A system, method, and computer-readable medium are disclosed forperforming a physical part identification generation operation. Thephysical part identification generation operation generates parts withan encoded geometry that passively represents information. In certainembodiments, the encoded geometry of the physical part uniquelyidentifies the part. In certain embodiments, the encoded geometrycomprises a plurality of multi-dimensional symbols (referred to asglyphs) which are combined to provide a unique multi-dimensionalidentifier. In certain embodiments, each multi-dimensional symbol is athree dimensional symbol and the encoded geometry is a three dimensionalpart comprising a plurality of the three dimensional symbols. In certainembodiments, the unique multi-dimensional identifier is a passive partwhich is synthesized during production. In certain embodiments, thepassive part that is attached to a component being identified such as aninformation handling system. In certain embodiments, the passive partincludes a bezel of the information handling system.

For purposes of this disclosure, an information handling system mayinclude any instrumentality or aggregate of instrumentalities operableto compute, classify, process, transmit, receive, retrieve, originate,switch, store, display, manifest, detect, record, reproduce, handle, orutilize any form of information, intelligence, or data for business,scientific, control, or other purposes. For example, an informationhandling system may be a personal computer, a network storage device, orany other suitable device and may vary in size, shape, performance,functionality, and price. The information handling system may includerandom access memory (RAM), one or more processing resources such as acentral processing unit (CPU) or hardware or software control logic,ROM, and/or other types of nonvolatile memory. Additional components ofthe information handling system may include one or more disk drives, oneor more network ports for communicating with external devices as well asvarious input and output (I/O) devices, such as a keyboard, a mouse, anda video display. The information handling system may also include one ormore buses operable to transmit communications between the varioushardware components.

FIG. 1 is a generalized illustration of an information handling system100 that can be used to implement the system and method of the presentinvention. The information handling system 100 includes a processor(e.g., central processor unit or “CPU”) 102, input/output (I/O) devices104, such as a display, a keyboard, a mouse, and associated controllers,a hard drive or disk storage 106, and various other subsystems 108. Invarious embodiments, the information handling system 100 also includesnetwork port 110 operable to connect to a network 140, which is likewiseaccessible by a service provider server 142. The information handlingsystem 100 likewise includes system memory 112, which is interconnectedto the foregoing via one or more buses 114. System memory 112 furthercomprises operating system (OS) 116 and in various embodiments may alsocomprise at least one of a physical part identification generationmodule 118 and a physical part detection module 120.

The physical part identification generation module 118 performs aphysical part identification generation operation. The physical partidentification generation operation generates physical parts with anencoded geometry that passively represents information. In certainembodiments, the encoded geometry of the physical part uniquelyidentifies the physical part. In certain embodiments, the encodedgeometry comprises a plurality of multi-dimensional symbols (referred toas glyphs) which are combined to provide a unique multi-dimensionalidentifier. In certain embodiments, each multi-dimensional symbol is athree dimensional symbol and the encoded geometry is a three dimensionalpart comprising a plurality of the three dimensional symbols. In certainembodiments, the unique multi-dimensional identifier is a passive partwhich is synthesized during production. In certain embodiments, thepassive part that is attached to a component being identified such as aninformation handling system. In certain embodiments, the passive partincludes a bezel of the information handling system.

The physical part detection module 120 performs a physical partdetection operation. The physical part detection operation detectsinformation encoded within an encoded geometry. In certain embodiments,the physical part detection operation includes decoding an encodedgeometry, comprising: scanning an encoded geometry, the scanningcomprising scanning a plurality of multi-dimensional symbols of theencoded geometry; identifying each of the plurality of multi-dimensionalsymbols; decoding each identifier multi-dimensional symbol to provideencoded geometry information; accessing an encoded geometry repository;and, retrieving data associated with the encoded geometry information.

FIG. 2 is a block diagram of a physical part identification environment200 implemented in accordance with an embodiment of the invention. Thephysical part identification environment 200 includes at least one of aphysical part identification generation system 118 as well as a physicalpart detection system 120.

In various embodiments, a user 202 generates a request to generate aunique encoded geometry. The request is received by the physical partidentification generation system 118. In various embodiments, a physicalpart identification generation system 118 executes on a hardwareprocessor of an information handling system 100. In these and otherembodiments, the user 202 may use a user device 204 to interact with atleast one of the physical part identification generation system 118 andthe physical part detection system 120.

As used herein, a user device 204 refers to an information handlingsystem such as a personal computer, a laptop computer, a tabletcomputer, a personal digital assistant (PDA), a smart phone, a mobiletelephone, or other device that is capable of communicating andprocessing data. In various embodiments, the user device is configuredto present a product query analysis user interface 240. In variousembodiments, the product query analysis user interface 240 presents aranked list of products 242 automatically generated in response to auser query. In various embodiments, the user device 204 is used toexchange information between the user 202 and the product query analysissystem 118 through the use of a network 140. In certain embodiments, thenetwork 140 may be a public network, such as the Internet, a physicalprivate network, a wireless network, a virtual private network (VPN), orany combination thereof. Skilled practitioners of the art will recognizethat many such embodiments are possible and the foregoing is notintended to limit the spirit, scope or intent of the invention.

In various embodiments, the physical part identification generationsystem 118 includes a physical part identification generation module 210which performs a physical part identification generation operation. Invarious embodiments, the physical part detection system 120 includes aphysical part detection module 212 which performs a physical partdetection operation. In various embodiments, the physical partidentification environment 200 includes a storage repository 220. Thestorage repository may be local to the system executing the productquery analysis system 118 or may be executed remotely. In variousembodiments, the storage repository includes one or more of an encodedgeometry repository 222 and a unique identifier repository 224.

In various embodiments, the physical part identification generationsystem 118 interacts with a product configuration system 250 which maybe executing on a separate information handling system 100. In variousembodiments, one or both of the physical part identification generationsystem 118 and the product configuration system 250 interact with acustom product fabrication system 252. In various embodiments, thecustom product fabrication system 252 fabricates products to includecomponents configured using the physical part identification generationsystem 118.

By digitally manufacturing the bezel, the physical part identificationgeneration operation provides flexibility to dynamically change the formof the bezel. When produced in a way that can be scanned similar to abarcode, the bezel provides an aesthetic and structuralmulti-dimensional part that can also be used to store information like aservice tag. The bezel becomes a storage device. The part itself is thecode and because it is multi-dimensional, the part has the potential tostore even more useful information than traditional barcodes. Certainembodiments use machine learning such that a user can now approach adevice having such a bezel and instructions executing on a user devicecan scan the bezel and read the part to retrieve useful information. Incertain embodiments, the part is read with the aid of an AugmentedReality device (e.g., an apparatus with the right sensors andcomputational power). Useful information may now gathered by observingthe part. In certain embodiments, a user device can scan the bezel,determine useful information about a device associated with the bezeland present the information to a user. In certain embodiments, theinformation presented to the user may be presented using augmentedreality. This useful information can include configuration informationof the information handling system, when the information handling systemwas produced, who ordered the information handling system, the servicetag of the information handling system, what faults are associated withthe information system, etc. In certain embodiments, the scanning usescloud point data (such as three dimensional cloud point data) whichallows dynamic movement while scanning and can also be scanned incomplete darkness.

In certain embodiments, the physical part identification generationoperation generates a number (x) of aesthetic assemblies using apredefined multi-dimensional design language (i.e., a glyph language).In certain embodiments, the physical part identification generationoperation provides a plurality of variations of the aesthetic assembliesthrough a machine learning operation. In certain embodiments, themachine learning operation can then generate new variations of aestheticassemblies based off of the patterns created to provide the newvariations with an inherited aesthetic.

In certain embodiments, each of the plurality of multi-dimensionalsymbols represents a respective numeric symbol. In certain embodiments,the numeric symbol is represented as a series of binary bits (e.g., asthree binary bits). In certain embodiments, the multi-dimensionalsymbols are arranged to represent a unique number set. In certainembodiments, the unique number set is associated with a serial number.In certain embodiments, the arrangement of multi-dimensional symbolsrepresents information such as the product service tag, SKU,manufacturer, date of production, etc.

In certain embodiments, during the physical part identificationgeneration operation, the multi-dimensional symbols are physicallysynthesized into a geometry of an object via a generative computer aideddesign (CAD) application. In certain embodiments, the object ismanufactured using digital manufacturing (such as 3D printing, CNCmachining, etc.). Digital manufacturing provides flexibility inproducing parts in a series much like bar codes. By producing parts thisway, passive objects are generated which are computer legible withoutthe need for additional identification information such as bar codes, QRcodes, printed alphanumeric serial numbers, etc. In certain embodiments,individual multi-dimensional symbols are produced suing traditionalmolding or machining and then assembled in a specific order to representa unique identifier. In certain embodiments, the multi-dimensionalsymbols are synthesized into structural and ornamental parts thusproviding aesthetically pleasing, uniquely encoded parts. It will beappreciated that an object having a plurality of the multi-dimensionalsymbols can symbolize more data than identifiers such as bar codes or QRcodes.

Such a physical part identification generation operation provides partswhich require no power to maintain or transmit data. Additionally, withsuch a physical part identification generation operation, parts aredigitally encoded as they are produced such that the parts do notrequire additional labeling processes. Additionally, with such aphysical part identification generation operation, the encoded parts canbe fabricated having the same color and material as the main body of theitem with which the part is associated, blending the encoded part intoitem. Additionally, with such a physical part identification generationoperation, the encoded parts provide detectable contrast from themulti-dimensional form rather than contrast from tint and shade as withidentifiers such as bar codes or QR codes. Additionally, with such aphysical part identification generation operation, the encoded parts aremore durable than a label. Additionally, with such a physical partidentification generation operation, the encoded parts are structuraland aesthetic parts that serve an additional function as a storagedevice (e.g., by providing information encoded into the part.Additionally, with such a physical part identification generationoperation, the encoded parts are computer legible.

FIG. 3 shows a high level flow chart of a physical part identificationgeneration operation 300. More specifically, the physical partidentification generation operation begins at step 310 by definingdesign parameters. In certain embodiments, the design parameters includeone or both of aesthetic parameters and geometric parameters.Additionally, at step 320, data to be encoded within the physical partare identified. In certain embodiments, the data to be encoded caninclude one or more of a serial number, a service tag, a manufactureridentifier, a part identifier, etc. In certain embodiments, the data tobe encoded is sequentially serialized for respective sequential encodedparts at step 324. Next at step 330, the data to be encoded is convertedto an encoded geometry. In certain embodiments, the encoded geometryincludes a plurality of multi-dimensional symbols. In certainembodiments, the data to be encoded and the associated encoded geometryare stored within an encoded geometry repository (such as repository222) at step 336.

Next, at step 340 a generative computer aided design operation isperformed using the design parameters and the encoded geometry. Thegenerative computer aided design operation provides a CAD object file345 which includes the encoded geometry. The CAD object file 345 is thenused to digitally fabricate a multi-dimensional part corresponding tothe design parameters and encoded geometry at step 350. In certainembodiments, the multi-dimensional part is used when manufacturing adevice such as an information handling system. In certain embodiments,the multi-dimensional part comprises a bezel of the information handlingsystem.

FIG. 4 shows a high level flow chart of a physical part detectionoperation 400. The physical part detection operation 400 begins at step410 by scanning a part having an encoded geometry. Next, each of theplurality of multi-dimensional symbols is identified at step 420. Nextat step 430, the physical part detection operation 400 accesses theencoded geometry repository 222 to retrieve data that was associatedwith the encoded geometry. Next at step 440, the physical part detectionoperation provides the data that was associated with the encodedgeometry.

Referring to FIG. 5, a front view of an example encoded geometry 500 isshown. The example encoded geometry corresponds to a bezel of aninformation handling system. More specifically, the encoded geometryincludes a plurality of multi-dimensional symbols 510 (i.e., glyphs). Asused herein, a glyph may be defined as an elemental symbol within anagreed set of symbols intended to represent a readable character for thepurpose of encoding and retrieving information. Also as used herein, aplurality of glyphs may be combined to collectively contribute toencoding and retrieving specific unique information.

Some of the multi-dimensional symbols represent a plurality ofconstrained values. In certain embodiments, the plurality of constrainedvalues for each glyph includes a two-dimensional value. In certainembodiments, the two-dimensional value is represented by a polygon. Incertain embodiments, the polygon comprises a hexagon.

In certain embodiments, plurality of constrained values for each glyphalso includes third-dimensional values. In certain embodiments, thethird-dimensional values include a depth. In certain embodiments, thethird-dimensional values include a slope associated with the depth.

In certain embodiments, at least one of the multi-dimensional symbolsincludes a fiducial marker symbol 530. In certain embodiments thefiducial marker system 530 includes a two-dimensional value. In certainembodiments, the two-dimensional value is represented by a polygon. Incertain embodiments, the polygon comprises a hexagon. In certainembodiments, the two-dimensional value of the fiducial marker symbol 530defines a regular hexagon (i.e., a hexagon that is both equilateral andequiangular). In certain embodiments, the fiducial marker includesthird-dimensional values. In certain embodiments, the third-dimensionalvalues include a depth. In certain embodiments, the third-dimensionalvalues include a slope associated with the depth.

Referring to FIG. 6, a flow chart of a multi-dimensional encodedgeometry generation operation 600 is shown. More specifically, themulti-dimensional generation operation starts at step 610 by identifyinglocked sides. Next at step 615, the multi-dimensional generationoperation identifies locked vertices. Next, at step 620 at least onevertex of one of the polygons within the encoded geometry is selected.Next, at step 630, the location of the selected vertex is adjustedcausing the polygon to change shape producing a warped polygon. Next, atstep 640, by changing the shape of the polygon associated with thevertex, the shapes of contiguous polygons are also changed producing aplurality of warped polygons. Next, at step 650, the multi-dimensionalgeneration operation 600 determines whether to select another vertex foradjustment. If so, then the multi-dimensional generation operation 600returns to step 620. If not, then the multi-dimensional generationoperation completes.

Referring to FIG. 7, line drawing views of example encoded geometries700, 702, 704 are shown. More specifically, the example encoded geometry700 includes a plurality of regular hexagonally shaped glyphs 706. Theexample encoded geometry 700 includes a plurality of locked sides 710.For the purposes of this disclosure, a locked side may be defined as aside of a polygon which remains unchanged even when a location of avertex within the encoded geometry is changed. The example encodedgeometry 700 also includes a plurality of locked points 712. For thepurposes of this disclosure, a locked point may be defined as a pointwithin the encoded geometry which remains unchanged even when a locationof a vertex within the encoded geometry is changed. It will beappreciated that providing one or both of locked sides and locked pointscontribute to the aesthetic parameters and geometry parameters of theencoded geometry. In certain embodiments, at least some of the lockedlines and locked points provide a fiducial marker symbol 720.

The example encoded geometry 702 includes a plurality of hexagonallyshaped glyphs 720 after the locations of certain vertexes 722 have beenadjusted. Adjusting the location of a particular vertex 724automatically adjusts the locations of the sides 726, 728 of the hexagonassociated with that vertex 724. Because these sides 726, 728 also forma part of two contiguous hexagons 730, 732, the shape of these hexagonsis also adjusted when the location of the particular vertex is adjusted.

The example encoded geometry 704 includes a plurality of hexagonallyshaped glyphs 720 after the locations of certain vertexes 742 have beenadjusted. Adjusting the location of a particular vertex 744automatically adjusts the locations of the sides 746, 748 of the hexagonassociated with that vertex 744. Because these sides 746, 748 also forma part of two contiguous hexagons 750, 752, the shape of these hexagonsis also adjusted when the location of the particular vertex is adjusted.

Referring to FIG. 8A, a line drawing showing an example of how a glyph800 may be encoded is shown. More specifically, each vertex of the glyph800 may be set to one of seven values. Six of the values represent alocation to which the vertex may be adjusted while the seventh valuerepresents an unadjusted location (i.e., the location of the vertex werethe hexagon a regular hexagon). By adjusting the locations of thevertexes, a single glyph can represent six numbers, each having sixpossible locations.

Accordingly, a single hexagonal glyph can encode and passively represent46656 different number combinations. FIG. 8B shows an example of thephysical glyph 850 corresponding to the glyph encoded according to theline drawing of FIG. 8A.

Referring to FIG. 9, a front view of a plurality of example encodedgeometries is shown. In the example, encoded geometries correspond tobezels of information handling systems mounted within a rack. Each bezelis generated by the physical part identification generation operation.Each bezel has a different encoded geometry where at least one inputvalue (e.g., at least one vertex of at least one glyph) of each encodedgeometry is different.

The front view of the plurality of example encoded geometries also showsan aesthetic advantage to having locked lines and vertexes whengenerating the encoded geometry. More specifically, because the toplines 910 and bottom lines 912 of a particular encoded geometry arelocked, when the information handling systems are mounted within a rack,the top lines 910 of one encoded geometry align with the bottom lines912 of a next higher encoded geometry. Additionally, the bottom lines912 of one encoded geometry align with the top lines 910 of a next lowerencoded geometry, providing an aesthetically pleasing substantiallycontinuous appearance across the mounted information handling systems.Additional, because the top vertexes 920 and bottom vertexes 922 of aparticular encoded geometry are locked, when the information handlingsystems are mounted in a rack, the top vertexes 920 of one encodedgeometry align with the bottom vertexes 922 of a next higher encodedgeometry. Additionally, the bottom vertexes 922 of one encoded geometryalign with the top vertexes 920 of a next lower encoded geometry,providing an aesthetically pleasing substantially continuous appearanceacross the mounted information handling systems. Additionally, a thirdvertex 924 on each side of the encoded geometry is located equidistantfrom the top vertex 920 and bottom vertex 922.

Referring to FIG. 10, a perspective view of portions of a plurality ofencoded geometries is shown. More specifically, each respective portion1010 of an encoded geometry includes a plurality of multi-dimensionalsymbols 1025. In certain embodiments, each of the plurality ofmulti-dimensional symbols is a respective glyph. Also, in certainembodiments, each encoded geometry includes a respective fiducialmulti-dimensional symbol 1030. The fiducial multi-dimensional symbol1030 provides a fixed basis of comparison when performing a physicalpart detection operation (such as the physical part detection operation400). Such encoded geometries provide computer legibility of aestheticor structural forms without the need for labeling or machine learning.In various embodiments, each encoded geometry is associated with acomponent. In certain embodiments, each encoded geometry is attached toa respective component.

It will be appreciated from the perspective view, that each of theplurality of multi-dimensional symbols 1025 includes a plurality ofvariations. In various embodiments, the plurality of variations includesa front two-dimensional variation, a rear two-dimensional variation, anda slope variation (i.e., the slope from the front of themulti-dimensional system 1025 to the rear of the multi-dimensionalsymbol 1025. It will be appreciated that in certain embodiments, theslope variation may be different for each side of the multi-dimensionalsymbol 1025. In certain embodiments, the plurality of variations isdetected by detecting information regarding the lines and vertices ofeach multi-dimensional symbol. In certain embodiments, detectinginformation regarding the vertices of the multi-dimensional symbolincludes detection of the location of each vertex of themulti-dimensional symbol. In certain embodiments, detecting informationregarding the lines of the multi-dimensional symbol includes detectionof a length of each line of the multi-dimensional symbol. In certainembodiments, detecting information regarding the lines of themulti-dimensional symbol includes detection of an angle at a vertexdefined by two lines of the multi-dimensional symbol.

It will also be appreciated from the perspective view, that the encodedgeometry provides dynamic legibility. For the purposes of thisdisclosure, dynamical legibility may be defined as a detection of athree dimensional form (e.g., the encoded geometry) which can presentdifferent information depending on a perspective variable or a proximityvariable when performing the detection. The proximity variable providesa certain resolution of the encoded geometry while the perspectivevariable shows a specific angle of the encoded geometry. Changing eitherof these variables provides a detection device with different inputs,which can provide different or additional decoded data. It will beappreciated that these variables may change even if only decoding atwo-dimensional portion of the three dimensional form such as the frontof the glyph or the rear of the glyph. For example, changing theproximity and perspective when decoding a two-dimensional portion of theencoded geometry results in variations of the proximity variables andthe perspective variables for a particular encoded geometry.

Referring to FIG. 11, a depth scanning representation from scanning ofportions of a plurality of encoded geometries is shown. In certainembodiments, the physical part detection operation decodes eachmulti-dimensional symbol into a legible character. In certainembodiments, when performing the physical part detection operation, adepth scanning operation is performed. In certain embodiments, the depthscanning operation is performed using a three dimensional scanningdevice. For the purposes of this disclosure, a three dimensionalscanning device is a device that analyses the plurality ofmulti-dimensional symbols 1025 of the encoded geometry and collects dataon the shape of each of the plurality of multi-dimensional symbols 1025of the encoded geometry. In certain embodiments, the scanning devicealso collects data on the appearance of the encoded geometry includingthe color of each of the multi-dimensional symbols. In certainembodiments, the depth scanning device produces dot patterns for each ofthe plurality of multi-dimensional systems 1025. In certain embodiments,the dot patterns may be produced based onto infrared (IR) dot patterns.

When performing the physical part detection operation, once the data onthe shape of each of the plurality of multi-dimensional symbols iscollected, this data can be used to retrieve data that was associatedwith the encoded geometry. Thus, the encoded geometry provides a passivestorage device via which information associated with the encodedgeometry may be retrieved.

In certain embodiments, the three dimensional scanning device includes astructured-light three dimensional scanning device. In operation, thestructured-light three dimensional scanning device projects a band oflight onto the encoded geometry to produce a line of illumination thatappears distorted from other perspectives from that of the projectedlight. This distorted line of illumination can then be used to producegeometric information regarding the encoded geometry. This geometricinformation is then used to exact geometric reconstruction of the shapeof the encoded geometry.

Referring to FIG. 12, a cloud point data representation from scanning ofportions of a plurality of encoded geometries is shown. In certainembodiments, when performing the depth scanning operation, point clouddata is generated. For the purposes of this disclosure, point cloud datacomprise a set of data points in a predefined multi-dimensionalcoordinate system. In certain embodiments, the predefinedmulti-dimensional coordinate system comprises a three-dimensionalcoordinate system where the set of data points are defined by X, Y and Zcoordinates to represent the external surface of each of the pluralityof multi-dimensional symbols. The set of data points can then be used toprovide an associated three-dimensional rendering of each of theplurality of multi-dimensional symbols. The three-dimensional renderingsmay then be analyzed to identify information associated with themulti-dimensional symbol. In certain embodiments, the analysis isperformed by the physical part detection module 212.

Referring to FIG. 13, an overlay representation of information obtainedfrom scanning of portions of a plurality of encoded geometries is shown.When performing the physical part detection operation, once the data onthe shape of each of the plurality of multi-dimensional symbols iscollected, this data can be used to retrieve data that was associatedwith the encoded geometry. For example, each of the plurality ofmulti-dimensional symbols 1025 has an associated value. In certainembodiments, the associated value comprises a multi-bit representation.In certain embodiments, the multi-bit representation comprises a 6-bitbinary representation. The combination of the plurality of multi-bitrepresentations provides unique, passively encoded information. Incertain embodiments, the unique passively encoded information is used toaccess information associated with the value from an encoded geometryrepository. Thus, the encoded geometry provides a passive storage devicevia which information associated with the encoded geometry may beretrieved.

Referring to FIGS. 14A and 14B, diagrammatic representations of apassively represented information environment 1400 is shown. Morespecifically, FIG. 14A shows a vertical orientation of items within athree-dimensional environment and FIG. 14B shows a horizontalorientation of items within a three-dimensional space. The passivelyrepresented information environment 1400 also includes a sensing device1410 (such as a camera) as well as a physical part detection system 1420(such as physical part detection system 120)

In certain embodiments, the three-dimensional space corresponds to aninformation technology (IT) data center and the items correspond toinformation handling systems and information handling system componentscontained within the data center. At least some of the informationhandling systems and information handling system components includeassociated encoded geometry (such as encoded geometry 500).

By providing the information handling systems and information handlingsystem components with associated encoded geometry, an automatic mappingof the information handling systems and information handling systemcomponents within the data center is enabled. Whereas, mapping of a datacenter could often be a meticulous process which involved users enteringand/or scanning unique identification information such as service tagsone by one, the mapping process may be performed efficiently via thephysical part detection system 1430. With previous mapping operations,once the unique identification information for each item in the datacenter was obtained, a three dimensional directory would need to becreated which would then be used to build a three-dimensionalrepresentation of the data center, matching the unique identificationinformation to a particular location within the data center. It will beappreciated that such a three-dimensional representation of a datacenter provides many advantages to managing the data center such asfinding and managing broken systems in a large data center. It would beadvantageous to be able to easily locate and identify informationhandling systems and information handling system components within thedata center.

With the disclosed passively represented information environment, eachof the items within the multi-dimensional space includes an associatedencoded geometry. Using a sensing device 1400, users can scan the itemsand easily recognize passively encoded information from afar. In certainembodiments, the sensing device can be included within an augmentedreality device. The passively encoded information can be decoded toprovide specific information regarding the associated item. In certainembodiments, the specific information can include unique identificationinformation such as a service tag. Additionally, the physical partdetection system 1430 can be used to map the locations of items withinthe three-dimensional space. In certain embodiments, the locations canalso be used to automatically generate a three-dimensionalrepresentation of the items within the multi-dimensional space which canbe archived for later use. Using the sensing device and thethree-dimensional representation, a user, such as an IT technician, canbe directed to a particular item within the three-dimensional space. Incertain embodiments, when the user is positioned at the rack the bezelshaving a desired item, the physical part detection system 1430 can beused to identify and highlight the desired item.

Using the sensing device 1410 and the physical part detection system1430, the surfaces that are visible within the three-dimensional spacevary depending on the sensing devices perspective. Knowing this,different information may be encoded and decoded from differentperspectives. The sensing device 1410 and the physical part detectionsystem 1430 can also determine the orientation and relative locations ofitems within the three-dimensional space based upon proximity andperspective determinations made by the sensing device 1410 and thephysical part detection system 1430. The orientation and relativelocation information can then be used to provide specific informationregarding items within the three-dimensional space.

In various embodiments, the sensing device 1410 and the physical partdetection system 1430 used to decipher these encoded geometries is alsoprogrammed to recognize the proximity and/or perspective of a pluralityof encoded geometries and provide users either high level or moredetailed information regarding items within the three-dimensional space.

For example, within a data center, an augmented reality portion of thephysical part detection system 1430 can represent the overall health ofa rack by augmenting items within the data center with a unique hue. Forexample, certain items might be augmented with a green hue to indicatethe item is functioning properly whereas other items might be augmentedwith an amber hue to indicate the time needs service. Using theaugmented reality portion of the physical part detection system 1430such an augmented representation enables a user to assess the overallhealth of a portion of a multi-dimensional space (e.g., a rack within adata center) from a distance. In certain embodiments, when a user getscloser to an item needing attention, only that individual item would behighlighted.

As another example, if an encoded geometry is the object that is encodedwith the passive information. The encoded geometry may be physicallylocked onto the item with which the encoded geometry is associated. Oncethe item is located using the physical part detection system 1430, auser could unlock and access a non-visible portion of the encodedgeometry. The encoded geometry is provided with more information whichis included as part of a non-visible portion of the encoded geometry. Invarious embodiments, this information can include information regardingcustom hardware configurations for the information handling system, suchas CPU type/model. In various embodiments, this information can includecustomer sensitive data such as who owns the information handlingsystem, who purchased the information handling system, when theinformation handling system was purchased, etc. In various embodiments,this information can include any sensitive data that is relevant to thesystem being observed and the customer who order it. Using this lockingfeature, the encoded geometry provides a physical level of encryptionfor an item associated with encoded geometry.

As another example, if the sensing device 1410 and the physical partdetection system 1430 determines that a user is standing in front of arack full of servers and that the user is reaching above their head topull out a system, the sensing device 1410 and the physical partdetection system 1430 can determine that the server being removed isabove the user and can generate a warning to be careful when removingthe system.

Referring to FIG. 15, a flow chart of an encoded geometry associationoperation 1500 is shown. More specifically, the encoded geometryassociation operation 1500 begins by indicating a number of items to beidentified at step 1510. In certain embodiments, the number of items tobe identified may be defined when the passively represented informationenvironment is originally configured. In certain embodiments, the numberof items to be identified may be defined when items are added to thepassively represented information environment. Next, at step 1520, anencoded geometry is associated with a particular item. Next, at step1530, encoded geometry information and the particular item with whichthe encoded geometry is associated are stored within a three-dimensionalspace encoded geometry repository. Next, at step 1540 the encodedgeometry association operation 1500 determines whether there are anyremaining items to be associated. If so, then the operation returns tostep 1520 to associate another item. If not, then the operation ends.

Referring to FIG. 16, a flow chart of physical part detection operation1600 within passively represented information environment is shown. Morespecifically, the operation begins at step 1610 by observing a portionof the multi-dimensional space (such as multi-dimensional space 1420).Next, at step 1620, the physical part detection operation 1600identifies parts within the physical space. In certain embodiments, theparts are identified via a physical part detection operation 400. Next,at step 1630, the physical part detection operation 1600 identifiesrelative locations of parts within the multi-dimensional space. Incertain embodiments, the physical part detection operation 1600 usesproximity information and perspective information to identify relativelocations of parts within the multi-dimensional space. The proximityinformation includes information regarding the physical nearness ofphysical parts. The perspective information includes informationregarding height, width, depth and relative position (e.g., is a partabove another part, below another part, to one side of another part, orto another side of another part) of physical parts.

Next, at step 1640, stores information for each item within thethree-dimensional space encoded geometry repository. Next, at step 1650,the physical part detection operation 1600 automatically generates athree-dimensional representation of the items within themulti-dimensional space. Next, at step 1660, the physical part detectionoperation 1600 provides information regarding items associated with thephysical parts. In certain embodiments, the information regarding itemsassociated with the encoded geometry can include augmented realityinformation.

Referring to FIG. 17, a flow chart of a multi-dimensional encodedgeometry machine learning operation 1700 is shown. In certainembodiments, the multi-dimensional machine learning operationfacilitates decoding of an encoded geometry. In certain embodiments, amachine learning operation begins at step 1710 by an informationhandling system such as a portable information handling system beingpositioned near a glyph. In certain embodiments, the informationhandling system comprises the sensor 1410 and the physical partdetection system 1430. In step 1715, the portable information handlingsystem identifies a glyph. In certain embodiment, the portableinformation handling system captures images or scans models of theglyphs, with each image or model depicting a glyph at an associatedangle and under certain lighting conditions. In step 1720, theinformation handling system stores the captured information with glyphinformation. In certain embodiments, the information handling systemstores a unique alphanumeric identifier corresponding to a glyph. Incertain embodiments, steps 1710-1720 may be repeated in a seconditeration relative to a glyph when the glyph is multi-dimensional. Thus,a first iteration may scan the glyph for a set of points correspondingto a first layer and a second iteration may scan the glyph for a set ofpoints corresponding to a second layer. In certain embodiments, thefirst set of points and the second set of points are in the samerelative positions, but the glyph has an associated distance between thefirst layer and the second layer. In certain embodiments, the set ofpoints in the first layer do not correspond to the set of point in thesecond layer. In these embodiments, the points in the first layer form afirst glyph and the points on the second layer form a different glyph.In certain embodiments, a first information handling system may beconfigured to scan just the first layer and a second informationhandling system may be configured to scan just the first layer, just thesecond layer or the first layer and the second layer.

Referring to FIG. 18, a flow chart of a multi-dimensional encodedgeometry decoding operation 1800 is shown. In step 1810, when theinformation handling system is positioned in front of a bezel havingmultiple glyphs and scans the bezel. In certain embodiments, theinformation handling system identifies multiple glyphs in a bezel byfirst identifying points in the bezel in step 1820. Next, in step 1830,the information handling system identifies shapes in the bezel based onthe scanned points. In certain embodiments in step 1836, the informationhandling system filters any points or shapes not necessary foridentifying a glyph in the bezel. The decoding operation crops points orshapes out of an image of a bezel, filters lines over a given length,filters shapes with three or more points in a row, or otherwise filtersany shape that does not correspond to a glyph. In step 1840, theinformation handling system compares the captured information withinformation stored in memory to identify each glyph. In certainembodiments, the information handling system compares captured shapeinformation with shape information stored in memory. Once theinformation handling system has identified a glyph, the informationhandling system determines system information associated with the glyphinformation. In some embodiments, the information handling systemdetermines one or more of the individual identifiers for each glyph ordetermines a single identifier associated with a plurality of glyphs.For example, in some embodiments in which each glyph is based on ahexagon with each vertex capable of being in a neutral point or any ofsix offset points, an individual identifier may be a simple string ofnumbers (e.g., 000000 for a glyph with all vertexes at neutralpositions, 012345 for a glyph with one vertex at a neutral position andthe other five vertexes at various offset points, etc.) or theinformation from two or more glyphs may be combined into fewer, but morecomplex identifiers.

Once the information handling system has identified all glyphs anddetermined a corresponding identifier or set of identifiers, theportable information handling system may use the information in step1840 to retrieve system information, historical data, servicinginstructions, upgrade options, and any other servicing and maintenancedata or instructions associated with the set of identifiers at step1850. In certain embodiments, the steps in any decoding operation may berepeated in a second iteration relative to the bezel when the bezel ismulti-dimensional. Thus, a first iteration may scan the bezel for a setof points corresponding to a first layer and a second iteration may scanthe bezel for a set of points corresponding to a second layer. Incertain embodiments, the first set of points and the second set ofpoints are in the same relative positions, but the glyph has a depthcomponent. However, the set of points on the first layer are notrequired to correspond to the set of point on the second layer. In theseembodiments, the points on the first layer form a first set of shapesand the points on the second layer form a different set of shapes. Incertain embodiments, a first information handling system may beconfigured to scan just the first layer and a second informationhandling system may be configured to scan just the first layer, just thesecond layer or the first layer and the second layer.

Those skilled in the art will appreciate that steps 1810-1830 may beperformed by a first information handling system and steps 1832-1850 maybe performed by a second information handling system.

Referring to FIG. 19, a representation 1900 of use of an augmentedreality device 1910 when decoding an encoded geometry 1915 is shown. Incertain embodiments, the augmented reality device 1910 comprises asensing device such as sensing device 1410. In certain embodiments, theencoded geometry 1915 corresponds to one of a plurality of bezels whereeach bezel is associated with a respective information handling systemwithin a rack of information handling systems 1920.

In certain embodiments, the augmented reality device 1910 generates amulti-dimensional encoded geometry screen presentation 1930. In certainembodiments, the multi-dimensional encoded geometry screen presentation1930 comprises a physical representation portion 1940 and a machinelearning presentation portion 1945. The physical representation portion1940 presents a view of the physical devices at which the augmentedreality device 1910 is directed. This view can represent one or more ofan angle at which the augmented reality device 1910 is directed relativeto the physical devices at which the augmented reality device 1910 isdirected, lighting conditions of the physical devices at which theaugmented reality device 1910 is directed and a context of the physicaldevices at which the augmented reality device 1910 is directed relative.In certain embodiments, the context shows one or more adjacent bezels.

In certain embodiments the machine learning presentation portion 1945comprises a glyph reading portion 1950 and a glyph identificationindication portion 1955. The glyph reading portion 1950 provides arepresentation of the physical glyphs on which the multi-dimensionalencoded geometry decoding operation is being performed. The glyphidentification indication portion 1955 provides a representation of theglyphs for which multi-dimensional encoded geometry decoding operationhas decoded the encoding within the glyph.

As will be appreciated by one skilled in the art, the present inventionmay be embodied as a method, system, or computer program product.Accordingly, embodiments of the invention may be implemented entirely inhardware, entirely in software (including firmware, resident software,micro-code, etc.) or in an embodiment combining software and hardware.These various embodiments may all generally be referred to herein as a“circuit,” “module,” or “system.” Furthermore, the present invention maytake the form of a computer program product on a computer-usable storagemedium having computer-usable program code embodied in the medium.

Any suitable computer usable or computer readable medium may beutilized. The computer-usable or computer-readable medium may be, forexample, but not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, ordevice. More specific examples (a non-exhaustive list) of thecomputer-readable medium would include the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a portable compact disc read-only memory (CD-ROM), anoptical storage device, or a magnetic storage device. In the context ofthis document, a computer-usable or computer-readable medium may be anymedium that can contain, store, communicate, or transport the programfor use by or in connection with the instruction execution system,apparatus, or device.

Computer program code for carrying out operations of the presentinvention may be written in an object oriented programming language suchas Java, Smalltalk, C++ or the like. However, the computer program codefor carrying out operations of the present invention may also be writtenin conventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Embodiments of the invention are described with reference to flowchartillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments of the invention. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, can be implemented by computerprogram instructions. These computer program instructions may beprovided to a processor of a general purpose computer, special purposecomputer, or other programmable data processing apparatus to produce amachine, such that the instructions, which execute via the processor ofthe computer or other programmable data processing apparatus, createmeans for implementing the functions/acts specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

The present invention is well adapted to attain the advantages mentionedas well as others inherent therein. While the present invention has beendepicted, described, and is defined by reference to particularembodiments of the invention, such references do not imply a limitationon the invention, and no such limitation is to be inferred. Theinvention is capable of considerable modification, alteration, andequivalents in form and function, as will occur to those ordinarilyskilled in the pertinent arts. The depicted and described embodimentsare examples only, and are not exhaustive of the scope of the invention.

Consequently, the invention is intended to be limited only by the spiritand scope of the appended claims, giving full cognizance to equivalentsin all respects.

What is claimed is:
 1. A computer-implementable method for facilitatingdecoding of an encoded geometry, comprising: scanning a plurality ofmulti-dimensional symbols, each of the plurality of multi-dimensionalsymbols being scanned from a plurality of angles; identifying each ofthe plurality of multi-dimensional symbols for each angle; and storinginformation identifying each of the plurality of multi-dimensionalsymbols for each angle in an encoded geometry repository.
 2. The methodof claim 1, wherein: scanning the plurality of multi-dimensional symbolscomprises multiple iterations, a first iteration identifying a firstsymbol and a second iteration identifying a second symbol.
 3. The methodof claim 1, wherein: the identifying each of the plurality ofmulti-dimensional symbols comprises: identifying a plurality of pointson a bezel; identifying a glyph corresponding to the plurality ofpoints, the glyph comprising glyph information; and comparing glyphinformation with information stored in the encoded geometry repository.4. The method of claim 1, wherein: the identifying each of the pluralityof multi-dimensional symbols comprises: identifying a plurality ofshapes in a bezel; identifying a glyph corresponding to the plurality ofshapes, the glyph comprising glyph information; and comparing glyphinformation with information stored in the encoded geometry repository.5. The method of claim 1, wherein: identifying each of the plurality ofmulti-dimensional symbols comprises one or more of filtering a set ofpoints and a set of shapes.
 6. The method of claim 1, furthercomprising: performing a machine learning operation, the machinelearning operation comprising the scanning and the identifying.
 7. Asystem for decoding an encoded geometry, comprising: a processor; a databus coupled to the processor; and a non-transitory, computer-readablestorage medium embodying computer program code, the non-transitory,computer-readable storage medium being coupled to the data bus, thecomputer program code interacting with a plurality of computeroperations and comprising instructions executable by the processor andconfigured for: scanning a plurality of multi-dimensional symbols, eachof the plurality of multi-dimensional symbols being scanned from aplurality of angles; identifying each of the plurality ofmulti-dimensional symbols for each angle; and storing informationidentifying each of the plurality of multi-dimensional symbols for eachangle in an encoded geometry repository.
 8. The system of claim 7,wherein: scanning the multi-dimensional symbol comprises multipleiterations, a first iteration identifying a first symbol and a seconditeration identifying a second symbol.
 9. The system of claim 7,wherein: the identifying each of the plurality of multi-dimensionalsymbols comprises: identifying a plurality of points on a bezel;identifying a glyph corresponding to the plurality of points, the glyphcomprising glyph information; and comparing glyph information withinformation stored in the encoded geometry repository.
 10. The system ofclaim 7, wherein: the identifying each of the plurality ofmulti-dimensional symbols comprises: identifying a plurality of shapesin a bezel; identifying a glyph corresponding to the plurality ofshapes, the glyph comprising glyph information; and comparing glyphinformation with information stored in the encoded geometry repository.11. The system of claim 7, wherein: identifying each of the plurality ofmulti-dimensional symbols comprises one or more of filtering a set ofpoints and a set of shapes.
 12. The system of claim 7, wherein theinstructions executable by the processor are further configured for:performing a machine learning operation, the machine learning operationcomprising the scanning and the identifying.
 13. A non-transitory,computer-readable storage medium embodying computer program code, thecomputer program code comprising computer executable instructionsconfigured for: scanning a plurality of multi-dimensional symbols, eachof the plurality of multi-dimensional symbols being scanned from aplurality of angles; identifying each of the plurality ofmulti-dimensional symbols for each angle; and storing informationidentifying each of the plurality of multi-dimensional symbols for eachangle in an encoded geometry repository.
 14. The non-transitory,computer-readable storage medium of claim 13, wherein: scanning theplurality of multi-dimensional symbols comprises multiple iterations, afirst iteration identifying a first symbol and a second iterationidentifying a second symbol.
 15. The non-transitory, computer-readablestorage medium of claim 13, wherein: the identifying each of theplurality of multi-dimensional symbols comprises: identifying aplurality of points on a bezel; identifying a glyph corresponding to theplurality of points, the glyph comprising glyph information; andcomparing glyph information with information stored in the encodedgeometry repository.
 16. The non-transitory, computer-readable storagemedium of claim 13, wherein: the identifying each of the plurality ofmulti-dimensional symbols comprises: identifying a plurality of shapesin a bezel; identifying a glyph corresponding to the plurality ofshapes, the glyph comprising glyph information; and comparing glyphinformation with information stored in the encoded geometry repository.17. The non-transitory, computer-readable storage medium of claim 13,wherein: identifying each of the plurality of multi-dimensional symbolscomprises one or more of filtering a set of points and a set of shapes.18. The non-transitory, computer-readable storage medium of claim 13,wherein the computer executable instructions are further configured for:performing a machine learning operation, the machine learning operationcomprising the scanning and the identifying.
 19. The non-transitory,computer-readable storage medium of claim 13, wherein: the computerexecutable instructions are deployable to a client system from a serversystem at a remote location.
 20. The non-transitory, computer-readablestorage medium of claim 13, wherein: the computer executableinstructions are provided by a service provider to a user on anon-demand basis.